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When a model contains COMPRESSION_METADATA but the interpreter was built without compression support, throw a RuntimeError with a helpful message directing users to build with --//:with_compression=true. The implementation uses inline functions in compression_utils.h that are optimized away when compression is disabled, ensuring all code paths remain compile-checked, and readable without preprocessor clutter. Includes test_compression_unsupported.py to verify the error detection, which only runs when compression is disabled. BUG=#3125
56 lines
No EOL
1.8 KiB
C++
56 lines
No EOL
1.8 KiB
C++
/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_LITE_MICRO_PYTHON_COMPRESSION_UTILS_H_
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#define TENSORFLOW_LITE_MICRO_PYTHON_COMPRESSION_UTILS_H_
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#include <cstring>
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#include "tensorflow/lite/schema/schema_generated.h"
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namespace tflite {
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// Returns true if interpreter was built with compression support.
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// When USE_TFLM_COMPRESSION is defined, this always returns true and
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// the compiler can optimize away any if (!IsCompressionSupported()) branches.
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inline constexpr bool IsCompressionSupported() {
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#ifdef USE_TFLM_COMPRESSION
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return true;
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#else
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return false;
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#endif
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}
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// Helper to check if model has compression metadata.
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// This is always compiled in, but when used with IsCompressionSupported()
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// the entire check can be optimized away.
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inline bool HasCompressionMetadata(const Model& model) {
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if (!model.metadata()) {
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return false;
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}
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for (size_t i = 0; i < model.metadata()->size(); ++i) {
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const auto* metadata = model.metadata()->Get(i);
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if (metadata && metadata->name() &&
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strcmp(metadata->name()->c_str(), "COMPRESSION_METADATA") == 0) {
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return true;
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}
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}
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return false;
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}
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} // namespace tflite
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#endif // TENSORFLOW_LITE_MICRO_PYTHON_COMPRESSION_UTILS_H_
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